Nowadays, Dynamic industries like tourism is a enhance to boost many countries economy in recent years. The hotel sector leads to a significant role among all aspects of the tourism industry. Online travel platforms, in association with hotel management, are a part of hotel E-tourism that helps users to make travel plans online, suggest precise recommendations in consideration with the earlier feedbacks upon hotel stay. From the past few months, the user roaming ratio falls rapidly due to the COVID-19 Pandemic across the globe. In a business concern, this Pandemic affects all tourism sectors, specifically in the hotels’ occupancy. To retain business positions and attract the users in these problematic scenarios, hotel and travel platform management concerns about past preferences of users, which have a significant impact on gratification for a comfortable stay. The current market trends show that user reviews are playing a vital role to select a hotel based on a safe location. Our work tries to find and recommend the dimensions that contribute more towards higher satisfaction levels of users in Asian continental top tourism city hotels listed by the Master and VISA Inc survey with item collaborative filtering and regression techniques based on Tripadvisor reviews from social media in recent times. The outcome of the work is helpful for Asian continental hotel management to concentrate more on the dimensions for obtaining better reviews. From an online travel platform perspective, this work suggests the contexts for the travel recommender system to gain things effectively from users.

Nowadays Internet of Things (IoT) is the trending topic where we go. IoT is included in almost every device surrounded by us where valuable information is shared over the network to store it in the cloud or to transfer as a message alert to an individual. IoT devices generate a huge amount of data but only caring information is required and for that analytics needs to be performed. Analytics are reaching outside of the traditional datacenter towards the edge, where the IoT data is generated. So, here in this paper, the importance of secure data sharing over a network, generated by IoT devices is described and along with that the data flow between IoT and edge server is discussed, and the requirement of edge analytics is focused.

Fog computing is used for reducing the complexity level of a network architecture and processes the data in a fog node IoT Hub. The Internet of Things (IoT) will connect billions of devices, such as smart objects, which are heterogeneous in terms of hardware software and communication interfaces. The IoT has to this point grown as numerous vertical idea of the IoT, rather than focusing at the real creation of a highly interoperable infrastructure for the development of applications. For managing the various devices present in the hub we create an IP-based infrastructure so that the elements can be able to balance the diversified devices and the network elements are used to enhance the direct end to end communication which is much required. With all the above considerations we propose a Fog node i.e. an IoT hub that can be placed at the end of multiple networks thereby increasing the capability by implementing various functions such as allocation of resources border routers cache proxy servers etc. As the implementation of fog node is through the IoT hub here we would like to automate the resource allocation that takes place in the IoT hub

A web of things abstracts the likelihood of distantly interfacing and detecting correct questions (things) through the web. With regards to our house, this knowledge can be apropos consolidated to brand it more intelligent, extra secured and robotization IoT venture focuses on constructing a remote home safety framework which directs caution to the user by using web if there is an incidence of any intruder it raises an alert automatically. Moreover, the identical can be similarly utilized for the home automation by using an analogous organization of devices. The use developed by desiring this context over the relative kinds of prevailing settings is that alarm and the position sent by the Wi-Fi linked microcontroller oversaw context can be gotten by the client on the telephone on or after in the least separation regardless of his adaptable telephone is linked with the web or not. The microcontroller used as a present model is the TICC3220 Launchpad, which attends a fixed smaller measure regulator besides a nearby available Wi-Fi making use of all the electrical machinery inside the house can be measured and supervised.

The Internet of Things (IoT) introduces an inventive and perceptive of a future Internet where users, computing systems, and everyday items owning sensing and actuating abilities cooperate with unique comfort and financial advantages. Many heterogeneous devices get connected and contribute to the IoT and are known as things. Internet of Things (IoT) enables these things to correspond, compute and make decisions on the network. In such a heterogeneous environment, every user of IoT will have a unique purpose to be served in the form of communication and computation. There is a threat that a malicious user can demolish the security and privacy of the network. Hence any application in the environment of IoT is prone to various attacks and threats. At this point, security becomes a high priority in IoT. To ensure security, care must be taken to guarantee confidentiality, authenticity, data integrity and non-repudiation. In this paper address various conventional techniques for providing security of IoT devices and present analysis of existing solutions for IoT. Firstly, as security will be a fundamental allowing thing of most IoT applications, mechanisms must also be designed to defend communications enabled by such technologies. Later, we identify some suitable security algorithms.

Application virtualization platforms are virtualization technologies that allow applications to run independently. It is observed that applications running on application virtualization platforms may have abnormal working conditions from time to time. However, such situations can be caught by system administrators examining the application log files in detail. This causes abnormal operating conditions to be captured long after they occur. Within the scope of this research, a method that allows to detect abnormal running conditions of applications running on application virtualization platforms in real time is proposed. The proposed method uses both unsupervised learning and supervised learning algorithms together. A prototype application was developed to demonstrate the usability of the proposed method. In order to demonstrate the success of the method, the tests we performed on the prototype yielded high accuracy in a real-time detection of abnormal operating conditions.

Smart cities are planned to have millions of Internet-connected sensors and devices. Sensors can create a huge amount of data in a range of applications. In modern urban environments, quality of life in a Smart City is heavily dependent on the safety of its residents. For a long time, public safety has been a major source of anxiety. For everyone, stopping a breach of private space security has become a priority. Traditional security systems raise an alarm whenever they detect a breach of safety. It is possible to find a breach of an advanced model by using image processing and a deep analysis of convolutional neural networks to classify images. Because of the ability to reduce complicated aspects from photographs using exact algorithms for facial and body detection. The results of specific machine learning, such as deep learning techniques are outstanding. The processing time of the proposed system is reduced, and true rate of face recognition is 72.7% under varying distance from 2m to 5m.This paper aims to show that when used together the security sector, the two can achieve more than might have been previously assumed models.

No abstract